Literature DB >> 15937768

Accuracy, precision, and consistency of expert HIV type 1 genotype interpretation: an international comparison (The GUESS Study).

Andrew R Zolopa1, Laura C Lazzeroni, Alex Rinehart, Françoise Brun Vezinet, François Clavel, Ann Collier, Brian Conway, Roy M Gulick, Mark Holodniy, Carlo-Frederico Perno, Robert W Shafer, Douglas D Richman, Mark A Wainberg, Daniel R Kuritzkes.   

Abstract

BACKGROUND: Resistance testing is considered standard of care in HIV medicine, but there is no standard interpretation system for genotype tests. We sought to determine how much agreement exists within a group of experts in the interpretation of complex genotypes.
METHODS: Genotypes from clinical specimens were sent to an international panel of 12 resistance experts. Phenotypic susceptibility testing of these clinical isolates was performed with antivirogram. Experts predicted phenotype fold change category (<2.5-fold change, 2.5-4.0-fold change, >4.0- to 7.0-fold change, >7.0- to 10-fold change, >10- to 20-fold change, or >20-fold change) and predicted expected drug activity for each of 16 antiretroviral drugs. Experts were also asked to make treatment recommendations on the basis of the genotype.
RESULTS: The experts predicted the exact phenotype fold change category correctly 44% of the time, but they varied widely by antiretroviral drug (range, 25%-74%). The highest accuracy was observed for lamivudine (74%) and the nonnucleoside reverse transcriptase inhibitors (66%-69%). Experts generally predicted higher levels of resistance to the remaining nucleoside reverse transcriptase inhibitors than what was found by phenotypic testing. Agreement among experts in predicting phenotype fold change category ranged widely depending on the drug (median agreement, 42% [range, 28%-74%]); the same pattern was observed in predicting expected drug activity (median agreement, 45% [range, 32%-87%]). Experts agreed on treatment recommendations in a median of 79% of instances, and recommendations were consistent over time, with blinded retesting.
CONCLUSIONS: Although their ability to predict phenotype from a genotype varied for individual antiretroviral drugs, this expert panel had a high degree of agreement in deriving treatment recommendations from the genotype.

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Year:  2005        PMID: 15937768     DOI: 10.1086/430706

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


  4 in total

1.  Significantly improved HIV inhibitor efficacy prediction employing proteochemometric models generated from antivirogram data.

Authors:  Gerard J P van Westen; Alwin Hendriks; Jörg K Wegner; Adriaan P Ijzerman; Herman W T van Vlijmen; Andreas Bender
Journal:  PLoS Comput Biol       Date:  2013-02-21       Impact factor: 4.475

Review 2.  Clinical management of HIV drug resistance.

Authors:  Karoll J Cortez; Frank Maldarelli
Journal:  Viruses       Date:  2011-04-14       Impact factor: 5.048

3.  Should we include connection domain mutations of HIV-1 reverse transcriptase in HIV resistance testing.

Authors:  Matthias Götte
Journal:  PLoS Med       Date:  2007-12       Impact factor: 11.069

4.  Connection domain mutations N348I and A360V in HIV-1 reverse transcriptase enhance resistance to 3'-azido-3'-deoxythymidine through both RNase H-dependent and -independent mechanisms.

Authors:  Maryam Ehteshami; Greg L Beilhartz; Brian J Scarth; Egor P Tchesnokov; Suzanne McCormick; Brian Wynhoven; P Richard Harrigan; Matthias Götte
Journal:  J Biol Chem       Date:  2008-06-10       Impact factor: 5.157

  4 in total

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